Single-cell RNA-seq data of human PBMC from Myasthenia Gravis patients
Single-cell RNA-seq · human · 40 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Homo sapiens (human)
- Samples
- 40 samples: 10 × AChR-positive MG vs 10 × Healthy control vs 10 × Seronegative MG pre-treatment vs 10 × Seronegative MG post-treatmentGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
- Paper
- B-cell immune dysregulation with low soluble CD22 levels in refractory seronegative myasthenia gravisFrontiers in immunology · 2024
Read the full summary ↓
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE227835_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA964702 and SRA study SRP435413. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 40 samples.
How we read this: 4 replicated groups read from 40 sample titles; they account for 40 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM7266236 AChR-positive MG_1 AChR-positive MG
- GSM7266237 AChR-positive MG_10 AChR-positive MG
- GSM7266238 AChR-positive MG_2 AChR-positive MG
- GSM7266239 AChR-positive MG_3 AChR-positive MG
- GSM7266240 AChR-positive MG_4 AChR-positive MG
- GSM7266241 AChR-positive MG_5 AChR-positive MG
- GSM7266242 AChR-positive MG_6 AChR-positive MG
- GSM7266243 AChR-positive MG_7 AChR-positive MG
- GSM7266244 AChR-positive MG_8 AChR-positive MG
- GSM7266245 AChR-positive MG_9 AChR-positive MG
- GSM7266246 Healthy control_1 Healthy control
- GSM7266247 Healthy control_10 Healthy control
- GSM7266248 Healthy control_2 Healthy control
- GSM7266249 Healthy control_3 Healthy control
- GSM7266250 Healthy control_4 Healthy control
- GSM7266251 Healthy control_5 Healthy control
- GSM7266252 Healthy control_6 Healthy control
- GSM7266253 Healthy control_7 Healthy control
- GSM7266254 Healthy control_8 Healthy control
- GSM7266255 Healthy control_9 Healthy control
- GSM7266256 Seronegative MG pre-treatment_10 Seronegative MG pre-tre…
- GSM7266257 Seronegative MG post-treatment_10 Seronegative MG post-tr…
- GSM7266258 Seronegative MG pre-treatment_1 Seronegative MG pre-tre…
- GSM7266259 Seronegative MG post-treatment_1 Seronegative MG post-tr…
- GSM7266260 Seronegative MG pre-treatment_2 Seronegative MG pre-tre…
- GSM7266261 Seronegative MG post-treatment_2 Seronegative MG post-tr…
- GSM7266262 Seronegative MG pre-treatment_3 Seronegative MG pre-tre…
- GSM7266263 Seronegative MG post-treatment_3 Seronegative MG post-tr…
- GSM7266264 Seronegative MG pre-treatment_4 Seronegative MG pre-tre…
- GSM7266265 Seronegative MG post-treatment_4 Seronegative MG post-tr…
- GSM7266266 Seronegative MG pre-treatment_5 Seronegative MG pre-tre…
- GSM7266267 Seronegative MG post-treatment_5 Seronegative MG post-tr…
- GSM7266268 Seronegative MG pre-treatment_6 Seronegative MG pre-tre…
- GSM7266269 Seronegative MG post-treatment_6 Seronegative MG post-tr…
- GSM7266270 Seronegative MG pre-treatment_7 Seronegative MG pre-tre…
- GSM7266271 Seronegative MG post-treatment_7 Seronegative MG post-tr…
- GSM7266272 Seronegative MG pre-treatment_8 Seronegative MG pre-tre…
- GSM7266273 Seronegative MG post-treatment_8 Seronegative MG post-tr…
- GSM7266274 Seronegative MG pre-treatment_9 Seronegative MG pre-tre…
- GSM7266275 Seronegative MG post-treatment_9 Seronegative MG post-tr…
- GSE267023 scRNA-seq analysis of PBMCs from ischemic stroke patients 16 samples shares pbmc, rna-seq
- GSE279945 OP3: single-cell multimodal dataset in PBMCs for perturbation prediction benchmarking 102 samples shares pbmc, single-cell
- GSE296117 A single-cell RNA-seq dataset of synovial fluid from rheumatoid arthritis treated with TNF-α/JAK inhibitor 18 samples shares single-cell, rna-seq
- GSE327167 Single-cell RNA-seq profiling of pleural mesothelioma and comparator pleural specimens 113 samples shares single-cell, rna-seq
- GSE318490 Single-cell RNA-seq of tumor samples from six advanced HGSOC patients across treatment stages (pre-NACT, post-NACT and platinum-sensitive recurrence) 10 samples shares single-cell, rna-seq
- GSE287301 Single-cell RNA-sequencing of HNSCC-infiltrating T cells 48 samples shares single-cell, rna-seq
- GSE269877 Single-cell RNA-sequencing of BCG naïve and recurrent non-muscle invasive bladder cancer reveals a CD6/ALCAM-mediated immune-suppressive pathway 38 samples shares single-cell, rna-seq
- GSE294300 Single-cell gene expression profiles of cells from primary colorectal cancer and adjacent normal tissue [scRNA-Seq] 36 samples shares single-cell, rna-seq
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.